13 citations · 85 across the 35 of their papers we have counts for
37 papers
From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health
He Hu, Yucheng Zhou, Qianning Wang +8
The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, high cost, stigma, and privacy c…
SonicWeave: Chunk-Routed Mixture-of-Experts for Unified Audio Scene Generation
Yunrui Cai, Xu Li, Yucheng Zhou +8
Text-conditioned general audio generation is moving beyond isolated speech, music, and sound-effect synthesis toward a single model that can compose them into controllable, coheren…
CARE: Causally-Aligned Reasoning Exploration for Medical Large Language Models
Yucheng Zhou, Peng Luo, Qianning Wang +2
Large Language Models (LLMs) have shown strong potential for medical reasoning, yet the scarcity and cost of expert-annotated data constrain their progress. While reinforcement lea…
Sim4Seg: Boosting Multimodal Multi-disease Medical Diagnosis Segmentation with Region-Aware Vision-Language Similarity Masks
Lingran Song, Yucheng Zhou, Jianbing Shen
Despite significant progress in pixel-level medical image analysis, existing medical image segmentation models rarely explore medical segmentation and diagnosis tasks jointly. Howe…
TheraMind: A Strategic and Adaptive Agent for Longitudinal Psychological Counseling
He Hu, Chiyuan Ma, Qianning Wang +5
The shortage of mental health professionals has driven the web to become a primary avenue for accessible psychological support. While Large Language Models (LLMs) offer promise for…
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models
Weigao Sun, Jiaxi Hu, Yucheng Zhou +12
Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer m…
MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration
Yucheng Zhou, Lingran Song, Jianbing Shen
Recent advancements in medical Large Language Models (LLMs) have showcased their powerful reasoning and diagnostic capabilities. Despite their success, current unified multimodal m…
ComplexBench-Edit: Benchmarking Complex Instruction-Driven Image Editing via Compositional Dependencies
Chenglin Wang, Yucheng Zhou, Qianning Wang +2
Text-driven image editing has achieved remarkable success in following single instructions. However, real-world scenarios often involve complex, multi-step instructions, particular…
Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation
Yucheng Zhou, Jiahao Yuan, Qianning Wang
Recent advancements in text-to-image (T2I) generation have enabled models to produce high-quality images from textual descriptions. However, these models often struggle with comple…
Safety Alignment via Constrained Knowledge Unlearning
Zesheng Shi, Yucheng Zhou, Jing Li
Despite significant progress in safety alignment, large language models (LLMs) remain susceptible to jailbreak attacks. Existing defense mechanisms have not fully deleted harmful k…
Self-Rewarding Large Vision-Language Models for Optimizing Prompts in Text-to-Image Generation
Hongji Yang, Yucheng Zhou, Wencheng Han +1
Text-to-image models are powerful for producing high-quality images based on given text prompts, but crafting these prompts often requires specialized vocabulary. To address this,…
Beyond Empathy: Integrating Diagnostic and Therapeutic Reasoning with Large Language Models for Mental Health Counseling
He Hu, Yucheng Zhou, Juzheng Si +6
Large language models (LLMs) hold significant potential for mental health support, capable of generating empathetic responses and simulating therapeutic conversations. However, exi…
DC-ControlNet: Decoupling Inter- and Intra-Element Conditions in Image Generation with Diffusion Models
Hongji Yang, Wencheng Han, Yucheng Zhou +1
In this paper, we introduce DC (Decouple)-ControlNet, a highly flexible and precisely controllable framework for multi-condition image generation. The core idea behind DC-ControlNe…
EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
He Hu, Lianzhong You, Hongbo Xu +7
With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (EI) capabilities is essential for enabl…
Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback
Yucheng Zhou, Lingran Song, Jianbing Shen
Existing Medical Large Vision-Language Models (Med-LVLMs), encapsulating extensive medical knowledge, demonstrate excellent capabilities in understanding medical images. However, t…
Diffusion Model with Representation Alignment for Protein Inverse Folding
Chenglin Wang, Yucheng Zhou, Zijie Zhai +2
Protein inverse folding is a fundamental problem in bioinformatics, aiming to recover the amino acid sequences from a given protein backbone structure. Despite the success of exist…
Impromptu Cybercrime Euphemism Detection
Xiang Li, Yucheng Zhou, Laiping Zhao +2
Detecting euphemisms is essential for content security on various social media platforms, but existing methods designed for detecting euphemisms are ineffective in impromptu euphem…
Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral Constraints
Guanjie Chen, Xinyu Zhao, Yucheng Zhou +3
Diffusion Transformers (DiT) have emerged as a powerful architecture for image and video generation, offering superior quality and scalability. However, their practical application…
Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models
Yucheng Zhou, Zhi Rao, Jun Wan +1
Large Vision-Language Models (LVLMs) excel in cross-model tasks but experience performance declines in long-context reasoning due to overreliance on textual information and reduced…
SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information
Jiashuo Sun, Jihai Zhang, Yucheng Zhou +3
Large Vision-Language Models (LVLMs) have become pivotal at the intersection of computer vision and natural language processing. However, the full potential of LVLMs Retrieval-Augm…
MemoryMamba: Memory-Augmented State Space Model for Defect Recognition
Qianning Wang, He Hu, Yucheng Zhou
As automation advances in manufacturing, the demand for precise and sophisticated defect detection technologies grows. Existing vision models for defect recognition methods are ins…
InsectMamba: Insect Pest Classification with State Space Model
Qianning Wang, Chenglin Wang, Zhixin Lai +1
The classification of insect pests is a critical task in agricultural technology, vital for ensuring food security and environmental sustainability. However, the complexity of pest…
Residual-based Language Models are Free Boosters for Biomedical Imaging
Zhixin Lai, Jing Wu, Suiyao Chen +2
In this study, we uncover the unexpected efficacy of residual-based large language models (LLMs) as part of encoders for biomedical imaging tasks, a domain traditionally devoid of…
MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution
Wei Tao, Yucheng Zhou, Yanlin Wang +3
In software development, resolving the emergent issues within GitHub repositories is a complex challenge that involves not only the incorporation of new code but also the maintenan…